[Congressional Record (Bound Edition), Volume 154 (2008), Part 4]
[House]
[Pages 5381-5386]
[From the U.S. Government Publishing Office, www.gpo.gov]




              CYTOLOGY PROFICIENCY IMPROVEMENT ACT OF 2008

  Mrs. CAPPS. Madam Speaker, I move that the House suspend the rules 
and pass the bill (H.R. 1237) to amend the Public Health Service Act to 
provide revised standards for quality assurance in screening and 
evaluation of gynecologic cytology preparations, and for other 
purposes, as amended.
  The Clerk read the title of the bill.
  The text of the bill is as follows:

                               H.R. 1237

       Be it enacted by the Senate and House of Representatives of 
     the United States of America in Congress assembled,

     SECTION 1. SHORT TITLE.

       This Act may be cited as the ``Cytology Proficiency 
     Improvement Act of 2008''.

     SEC. 2. REVISED STANDARDS FOR QUALITY ASSURANCE IN SCREENING 
                   AND EVALUATION OF GYNECOLOGIC CYTOLOGY 
                   PREPARATIONS.

       (a) In General.--Section 353(f)(4)(B)(iv) of the Public 
     Health Service Act (42 U.S.C. 263a(f)(4)(B)(iv)) is amended 
     to read as follows:
       ``(iv) requirements that each clinical laboratory--

       ``(I) ensure that all individuals involved in screening and 
     interpreting cytological preparations at the laboratory 
     participate annually in a continuing medical education 
     program in gynecologic cytology that--

       ``(aa) is approved by the Accrediting Council for 
     Continuing Medical Education or the American Academy of 
     Continuing Medical Education; and
       ``(bb) provides each individual participating in the 
     program with gynecologic cytological preparations (in the 
     form of referenced glass slides or equivalent technologies) 
     designed to improve the locator, recognition, and 
     interpretive skills of the individual;

       ``(II) maintain a record of the cytology continuing medical 
     education program results for each individual involved in 
     screening and interpreting cytological preparations at the 
     laboratory;
       ``(III) provide that the laboratory director shall take 
     into account such results and other performance metrics in 
     reviewing the performance of individuals involved in 
     screening and interpreting cytological preparations at the 
     laboratory and, when necessary, identify needs for remedial 
     training or a corrective action plan to improve skills; and
       ``(IV) submit the continuing education program results for 
     each individual and, if appropriate, plans for corrective 
     action or remedial training in a timely manner to the 
     laboratory's accrediting organization for purposes of review 
     and on-going monitoring by the accrediting organization, 
     including reviews of the continuing medical education program 
     results during on-site inspections of the laboratory.''.

       (b) Effective Date and Implementation; Termination of 
     Current Program of Individual Proficiency Testing.--
       (1) Effective date and implementation.--Except as provided 
     in paragraph (2), the amendment made by subsection (a) 
     applies to gynecologic cytology services provided on or after 
     the first day of the first calendar year beginning 1 year or 
     more after the date of the enactment of this Act, and the 
     Secretary of Health and Human Services (hereafter in this 
     subsection referred to as the ``Secretary'') shall issue 
     final regulations implementing such amendment not later than 
     270 days after such date of enactment.
       (2) Termination of current individual testing program.--The 
     Secretary of Health and Human Services shall terminate the 
     individual proficiency testing program established pursuant 
     to section 353(f)(4)(B)(iv) of the Public Health Service Act 
     (42 U.S.C. 263a(f)(4)(B)(iv)), as in effect on the day before 
     the date of the enactment of subsection (a), at the end of 
     the calendar year which includes the date of enactment of the 
     amendment made by subsection (a).

  The SPEAKER pro tempore. Pursuant to the rule, the gentlewoman from 
California (Mrs. Capps) and the gentleman from Georgia (Mr. Deal) each 
will control 20 minutes.
  The Chair recognizes the gentlewoman from California.


                             General Leave

  Mrs. CAPPS. Madam Speaker, I ask unanimous consent that all Members 
may have 5 legislative days to revise and extend their remarks and 
include extraneous material on the bill under consideration.
  The SPEAKER pro tempore. Is there objection to the request of the 
gentlewoman from California?
  There was no objection.
  Mrs. CAPPS. Madam Speaker, I yield myself such time as I may consume.
  Madam Speaker, I rise in support of H.R. 1237, the Cytology 
Proficiency Improvement Act of 2007. This legislation would modernize 
Federal regulations under the Clinical Laboratory Improvement 
Amendments Act of 1988, CLIA, that subject those who screen and 
interpret Pap tests to annual proficiency testing.
  In 2005, CMS launched a program to begin testing pathologists and 
other laboratory professionals who performed Pap tests for proficiency. 
However, the program was designed using regulations written in 1992. In 
the 13 years between the regulation and the program's start, 
significant investments were made in the science and practice of Pap 
tests. Instead of relying on outdated practices, H.R. 1237 draws on the 
best that science and technology has to offer.
  H.R. 1237 has 175 bipartisan cosponsors, including myself and every 
other female member of the Energy and Commerce Committee. Additionally, 
this bill is supported by the College of American Pathologists, the 
American Medical Association, the American Clinical Laboratory 
Association, the American College of Obstetricians and Gynecologists, 
and the American College of Nurse Midwives.
  I want to commend my colleagues, Representative Gordon and 
Representative Deal, for their hard work and commitment on this very 
important piece of legislation. This bill would improve the quality of 
women's health care. I strongly encourage all of our colleagues to join 
me in support of H.R. 1237.
  Madam Speaker, I reserve the balance of my time.
  Mr. DEAL of Georgia. Madam Speaker, I yield myself such time as I may 
consume.
  I, too, rise in support of the Cytology Proficiency Improvement Act. 
I was a sponsor of legislation similar to this in the last Congress 
which passed the House, but unfortunately it was never signed into law. 
The bill revises national quality assurance standards of laboratories 
responsible for cytology services.
  A few summers ago, I had the opportunity to visit a laboratory of a 
pathologist in my district, and I saw first hand the impact of this 
legislation. This bill is the result of actions taken in 2005 by the 
Centers for Medicare and Medicaid Services to institute a proficiency 
testing program for individual pathologists.

                              {time}  1530

  Unfortunately, this program was based on regulations first issued in 
1992 as a result of the Clinical Laboratory Improvement Amendments of 
1988. Thus the cytology proficiency program is now very outdated and 
based on regulations from nearly 15 years ago.
  The legislation would provide for an orderly phase-out of the current 
program and transition into a new program where all individuals 
involved in screening and interpreting Pap tests would participate in a 
continuing medical education program in gynecologic cytology. This 
educational approach will present participants with complex cases to 
keep their skills on the cutting edge and will provide individuals an 
opportunity to test their skills.
  I believe this legislation would be an important step in the right 
direction and would modernize the current regulatory framework while 
providing quality assurance, as was required in the Clinical Laboratory 
Improvement Amendments. Unlike last Congress, I hope we will be able to 
get this legislation signed into law in order to modernize an outdated 
proficiency testing program for pathologists.

[[Page 5382]]

  Madam Speaker, I reserve the balance of my time.
  Mrs. CAPPS. Madam Speaker, I continue to reserve the balance of my 
time.
  Mr. DEAL of Georgia. Madam Speaker, I am pleased to yield 5 minutes 
to my colleague from Georgia (Mr. Price), one of the original 
cosponsors of the legislation this year, a medical doctor.
  Mr. PRICE of Georgia. I thank my friend and colleague from Georgia, 
Congressman Deal, for his leadership on this issue and for the time 
today.
  I also want to express my gratitude and thanks to Representative 
Gordon, who was extremely cooperative and helpful and productive 
throughout this entire process. I want to thank the American College of 
Pathology and all of the pathologists across the Nation who are working 
day in and day out to make certain that they provide quality care for 
the patients for whom they are charged.
  Madam Speaker, I include in the Record a copy of an article by Dr. 
George Nagy that documents the dysfunctional federally mandated 
proficiency test in cytopathology.

       The Dysfunctional Federally Mandated Proficiency Test in 
                 Cytopathology--A Statistical Analysis

       Proficiency testing in cytopathology and in other 
     disciplines should be based on firm statistical and 
     scientific foundations, because test theory in general is a 
     heavily statistical subject. Statistical considerations have 
     demonstrated that the design of ``short'' proficiency tests 
     in cytopathology, including the current federally mandated 
     test, fundamentally is unsound because of the lack of 
     sufficient validity and reliability. Examinees too frequently 
     are misclassified by such short-format tests: Competent 
     examinees fail the test in surprisingly high numbers, whereas 
     most of the examinees who have insufficient cytologic skills 
     eventually pass the test after the allowed retakes. Only 
     dichotomous tests are suitable for accurate computation of 
     the effects of test design on reliability, but the 
     statistical conclusions also are generalizable to 
     nondichotomous tests. In conclusion, the current federally 
     mandated proficiency test cannot reliably measure the level 
     of expertise of cytologists and, thus, cannot assure that 
     only adequately skilled individuals evaluate Papanicolaou 
     test samples. To render the test suitable for its intended 
     purpose, the authors believe that complete redesign of the 
     test, with the participation of experts in modern test 
     theory, would be advisable.
       Proficiency testing in cytopathology (PTC), which was 
     established in the 1991 regulations to implement the Clinical 
     Laboratory Improvement Amendments of 1988 (CLlA'88), has only 
     recently been enforced on a national scale. For more than a 
     decade, during which logistical hurdles hampered the 
     development of a national program for PTC, there was not much 
     incentive to think about the value and potential of PTC or 
     its theoretical background or to worry that the test design 
     was so poor. In 2004, however, the Center for Medicare and 
     Medicaid Services announced that a national PTC program 
     developed by the Midwest Institute for Medical Education had 
     been approved and that the regulations finally would be 
     enforced on a national level. Suddenly, the shortcomings of 
     the test were everyone's problem. What followed was a flurry 
     of comments, articles, proposals, and Internet discussions 
     about the PTC and its future. Although the testing has 
     proceeded nationwide in conformity with the original 
     regulations, the dust has not yet settled on the subject. The 
     professional organizations agree that PTC, as prescribed in 
     CLIA'88, is inadequate and is in great need of improvement if 
     indeed it should remain in place at all. Regarding the 
     projected revisions, it is a real impediment that some 
     regulatory authorities that are in a position to make 
     decisions about the implementation of PTC apparently are not 
     familiar with most of the theoretical implications of test 
     theory, which is an exceedingly complicated subject. So long 
     as the test is mandatory for every practitioner of 
     gynecologic cytopathology in the United States, it is in the 
     best interest of all participants for PTC to become a 
     scientifically well-founded, valid, and reliable quality 
     assurance method. In the current article, we have attempted 
     to shed light on some gaps in the knowledge about the 
     theoretical underpinnings of PTC that seem to endure in the 
     cytopathology literature.


                       test theory is statistical

       Test theory is a heavily statistical subject. Virtually all 
     aspects of test theory have been investigated in depth almost 
     exclusively by educators and psychologists, which is 
     understandable, because testing is a central issue in their 
     disciplines. Unfortunately, this valuable body of literature 
     apparently has been disregarded completely by the federal 
     authorities that are responsible for PTC regulations.
       The statistical apparatus used in modern test theory is 
     formidable. Many books and articles written about the subject 
     use highly sophisticated mathematical tools, including 
     differential and integral calculus and matrix algebra. One of 
     the reasons for the high degree of mathematization of test 
     theory in psychology and education science is that these 
     disciplines deal largely with intangibles, like motivation, 
     intelligence, understanding, and adaptability, which are not 
     directly measurable. Such entities must be studied 
     indirectly, through measurements of other quantities. That is 
     why psychological test theory introduced the concept of 
     ``constructs'' that can substitute for and represent the 
     kinds of abstract attributes mentioned above. Even so, the 
     highly complicated mathematical and statistical tools that 
     have been promoted in educational and psychological test 
     theory fulfill mainly academic purposes. Most actual problems 
     in everyday testing can be solved on a practical level that 
     does not use highly complicated mathematical methods but, at 
     the same time, does not disregard basic statistical 
     principles.


             testing in the physical and biologic sciences

       Cytopathology, unlike educational science or psychology, is 
     an applied natural science, and this is one of the reasons 
     why PTC can be performed without the application of overly 
     sophisticated mathematical tools. Interpretation of 
     Papanicolaou smears, reproduction of cytologic diagnoses, and 
     measurement of false-negative proportions, among others, are 
     very complex tasks. By comparison, technically, it is a 
     comparatively straightforward matter to evaluate the 
     examinees' ability to assign diagnostic categories to 
     cytologic changes observed on a slide or computer screen. 
     Thus, abstract constructs hardly are needed in PTC. 
     Nevertheless, a certain level of mathematical and statistical 
     understanding by the designers of the test is crucial if a 
     fair and scientifically valid system of PTC is to be 
     established. Most pathologists, including ourselves, do not 
     have rigorous training in statistics; therefore, if PTC is to 
     continue, then the regulatory authorities ought to contract 
     with experts in statistics and test theory who, through 
     interaction with knowledgeable cytopathologists and 
     cytotechnologists, would design an equitable and 
     scientifically well-founded system for the nationwide PTC.
       We do not mean to suggest that statisticians have not 
     participated in the design of cytology testing programs. In 
     fact, the College of American Pathologists' (CAP) 
     Interlaboratory Comparison Program for Cervicovaginal 
     Cytology was designed, implemented, and monitored with the 
     extensive help of statistical expertise. However, this 
     educational endeavor was not intended to be a PTC program as 
     envisioned in the federal regulations. In fact, its original, 
     scientifically and statistically supported structure 
     ironically prevented its use as a PTC program because of the 
     specific requirements of the federal regulations.


                      short tests and reliability

       One of the central problems in the practice of PTC is 
     reliability, and the reliability of PTC is related closely to 
     the size of the test sets (the number of the test items or 
     challenges in 1 test set). ``Short'' tests, which require the 
     evaluation of relatively small numbers of slides, are 
     characterized by a high misclassification rate. (The 
     pervasive effect of sample size on the reliability of 
     statistical inference is the reason why pollsters use large 
     samples: The larger the sample, the narrower are the 
     confidence limits in relative terms. The statistical 
     estimates inferred from a single sizable sample that has been 
     chosen by randomization will approach the true parameters of 
     the population.) Short tests will not prevent the frequent 
     failure of competent examinees or the passing of examinees 
     who have less than desirable skill levels. Already in 1991 
     one of us (G.K.N.), in a report that was written with D.C. 
     Collins, emphasized that the expected misclassification rate 
     of such short tests can be surprisingly high and that, in the 
     case of dichotomous tests, this rate can be calculated (or 
     approximated) through the use of the binomial theory of 
     statistics. (A dichotomous test evaluates the responses to 
     test items as ``right'' or ``wrong,'' without using 
     intermediate results or weighing of answers. The PTC system 
     used in New York State for 36 years was dichotomous and so 
     was the original Interlaboratory Comparison Program in 
     Cervicovaginal Cytology. The CLIA'88-mandated PTC is not 
     dichotomous.) This so-called ``simple binomial error model'' 
     was described in test theory initially in the 1950s.
       The results of the CLIA'88 mandated national PTC in 2005 
     dramatically demonstrated the effect of misclassification 
     during short tests, as described previously. According to the 
     data from the National Cytology Proficiency Testing Update, 
     9% of the examinees failed the test when they attempted it 
     for the first time. However, when this group that supposedly 
     had inferior skills retook the test, curiously, the failure 
     rate for this second attempt was similar to that for the 
     entire original group (10%). It appears that the cytologic 
     skills among those examinees who had failed originally 
     improved miraculously, allowing 90% of them

[[Page 5383]]

     to pass the examination, although all of them initially 
     failed. It is hard to believe that a short remedial training 
     between the first and second attempt could result in such an 
     impressive real improvement. The only plausible scientific 
     explanation is the well-known statistical phenomenon, the 
     Galtonian ``regression toward the mean.'' The majority of 
     failures during the first attempt were the consequence of 
     misclassification because of the poor validity and 
     reliability of the short test and were not caused by the 
     insufficient skills of those who failed. The failure rate in 
     all groups of examinees is about the same on the first 
     attempt and on the second attempt, and previous failures do 
     not seem to matter much. Essentially, the results of the 
     CLIA'88-mandated PTC mostly mirror the statistical chances 
     and not the examinees' skills.
       Of course, multiple other variables beyond regression 
     toward the mean, including experience gained in the technique 
     of the test, differences in the difficulty of particular test 
     sets, and even increased skills after remedial training, etc, 
     also may play a role in the improvement of test results at 
     the second attempt for individual examinees. However, to 
     date, we do not have any data or even a plausible explanation 
     concerning how any of these other factors, with the exception 
     of regression toward the mean, could produce such a 
     consistent result.


                    The Simple Binomial Error Model

       Misclassification of examinees by any short test, including 
     the CLIA'88-mandated PTC, can be demonstrated by means of an 
     analogy. Strictly speaking, this analogy is applicable only 
     to dichotomous testing systems. However, in this sense, 
     dichotomous and non dichotomous systems are correspondent. 
     For statistical or evaluation purposes, non dichotomous 
     systems can be made dichotomous at any time, even after the 
     tests have been carried out. For example, an answer can be 
     evaluated as correct only if it falls into the appropriate 
     single category (``success'') and all other answers are rated 
     as wrong (``failure''). Another solution to this problem in 
     PTC would be to restrict the number of diagnostic categories 
     to 2, with 1 category, for instance, ``negative for 
     premalignant or malignant changes'' and the second category 
     ``premalignant or malignant lesions are present.'' This is 
     the approach used in the original CAP PAP program with its 
     ``100 series'' and ``200 series.''
       The CLIA'88 regulations concerning PTC, with their 4 
     diagnostic categories and complicated scoring system, do not 
     fit into the dichotomous scheme. Despite this fact, the 
     conclusions drawn by using the binomial error model regarding 
     PTC are applicable to any short test to a large extent.


                 Example of Simple Binomial Error Model

       For the purpose of illustration, let us suppose, that in a 
     large population (for instance, that of an entire country), 
     the results from a scrupulous statistical survey using many 
     thousands of questionnaires and proper randomization indicate 
     that the proportion of individuals who like to watch 
     television (TV) is 90%. Because the survey is conducted in a 
     scientific way and the sample size is very large, this result 
     is considered highly accurate. The basic question on which 
     the analogy with PTC will be based is, ``What can we expect 
     if we ask 10 randomly selected individuals in this population 
     about their attitude toward TV?'' The most probable result 
     will be that, in this population, 9 of 10 individuals will 
     like TV. However, it is reasonable to expect that, in many 
     samples that consist of 10 individuals, all 10 individuals 
     are TV fans; whereas, in other similar samples, there may be 
     only 8, 7, or 6 such individuals. However, it is hardly 
     conceivable that we will identify as few as only 1 or 2 fans 
     in a sample of 10 individuals if the principle of random 
     selection is followed.
       Random selection is important. For example, a nonrandom 
     sample, like one that consists exclusively of nuns in 
     convents, would not yield a statistically valid reflection of 
     the entire population; indeed, we may identify only 1 or 2 
     individuals in such a sample who like to watch TV. Exclusive 
     selection of nuns or members of any other group with some 
     special interest would not be compatible with the principle 
     of randomness. However, to select a nun occasionally in a 
     sample, with a frequency roughly corresponding to the 
     proportion of nuns in the entire population, would be 
     appropriate.
       There is a statistical method that uses the so-called 
     ``binomial formula'' for calculating the probability of 
     encountering 10, 9, 8, 7, etc, TV fans in a sample of 10 
     individuals from our postulated population. (This method is 
     not detailed in the current article, but an explanation can 
     be found in any elementary statistical textbook). The 
     probabilities even can be looked up in tables that are found 
     at the end of statistical books. Under the circumstances 
     outlined above (with a 90% proportion of TV fans in a sample 
     size of 10 individuals). the probabilities of identifying 10, 
     9, 8, 7, and 6 TV fans in a random sample of 10 individuals 
     are 0.35, 0.39, 0.19, 0.06, and 0.01, respectively.
       The probability of identifying 5 TV fans under the above-
     described circumstances in a truly random sample of 10 
     individuals is exceedingly small. The succession of numbers 
     described above represents a ``probability distribution,'' 
     which can be observed in a histogram. This distribution is 
     interpreted as follows: If, from this very large population, 
     we take numerous random samples, each consisting of 10 
     individuals, and ask about their preferences for TV; then we 
     will find that 35% of the samples would include 10 fans, 39% 
     of the samples would include 9 fans, 19% of the samples would 
     include 8 fans, and so on.
       If we change the size of the sample, then the magnitudes of 
     the single probabilities and their distribution also will 
     change and, along with them, the probability distribution. If 
     we choose sample sizes of 100 individuals instead of 10, then 
     the probabilities will be clustered much more tightly around 
     the value of 90% than was the case in the smaller samples. 
     The larger the size of the sample, the more reliable is the 
     estimation; in other words, the observed value in every 
     sample approaches the real population parameter. It is 
     virtually unimaginable that there will be only 50 or 60 TV 
     fans among 100 randomly selected individuals from this 
     population. (Distribution data for such large samples are not 
     provided even in the tables of larger statistical reference 
     books: They are not needed, because the probability 
     distribution for large samples can be found by the so-called 
     ``normal approximation of the binomial distribution.'' To 
     perform this method is mathematically simple, but the results 
     may be slightly inaccurate. There are complex Web-based 
     Internet tools, however, that calculate these probabilities 
     very accurately.) Of course this holds true only if the 
     randomness principle is strictly observed.
       How can we apply the reasoning described above to the issue 
     of sample sizes in PTC? Fortunately, the results of these 
     binomial calculations can be generalized. The reason why we 
     can do this is that, if the ``experiment'' qualifies as 
     binomial, then the specifics of the experiment, whether they 
     are related to liking TV or to success in PTC, have no 
     bearing on the values of the probabilities or on the 
     probability distribution.


                              True Scores

       At this point, we need to review the term ``true score,'' a 
     concept that is used widely in modern test theory. The true 
     score of a hypothetical examinee is defined as the average of 
     the observed or measured scores that would be obtained over 
     an infinite number of repeated testing by the same test, 
     provided that the examinee's skills remain indefinitely 
     stable. For actual examinees, the true score can be estimated 
     with a small error margin, but its exact value is essentially 
     unknowable. For instance, if a cytologist screens 100,000 
     cervical smears, and if his or her diagnoses are correct 
     98,000 times, then the approximation of his or her true score 
     is 0.98. Because the accurate determination of the true score 
     would require an infinite number of repeat testing, which is 
     not feasible, this true score of 0.98 remains an 
     approximation. Obviously, we can be rather sure that, when 
     the same individual screens the next 100,000 preparations, 
     the approximation of his or her true score will not remain 
     the same: The chances of this are infinitesimally small. The 
     estimate of the true score will almost certainly change 
     slightly, for instance to 0.97 or to 0.99, and so on, for 
     each successive trial.
       It has to be emphasized that assignment of an exact ``true 
     score'' to a cytologist is somewhat arbitrary for further 
     reasons. It cannot be expected that anybody's cytologic 
     skills will remain invariant for a prolonged time. We can 
     hope, of course, that the professional prowess of cytologists 
     improves over time. Furthermore, everybody who has ever 
     screened cytology specimens knows that screening performance 
     depends on many factors, some of which are extraneous to the 
     level of cytology skills. On a ``good'' day, a cytologist may 
     function on a 0.98 score level; whereas, on a different, 
     ``bad'' day, he or she might be less ``proficient.'' Even his 
     or her experience with particular kinds of cytologic 
     presentations on the previous day, for example, having seen 
     an unusual presentation of high-grade squamous 
     intraepithelial lesion on a quality-assurance review, could 
     affect decision-making on the current day. Of course, these 
     and other psychological variables (eg, the effects of anxiety 
     or tiredness during tests or routine work) cannot be factored 
     into the statistical considerations. Nagy and Collins, 
     describing this concept, used the term ``competence level'' 
     instead of ``true score'' in their 1991 article.
       Direct measurement of the true score is not possible. What 
     we have after an evaluation of test results is the ``observed 
     score,'' which is related to the true score but is not 
     identical to it. It can be considered an estimate of the true 
     score.


              Comparison of TV Preference and PTC Results

       TV preference and PTC results can be compared as follows: 
     The values derived by the binomial formula are determined 
     only by the number of trials and the probability of success. 
     If the ``experiment'' qualifies as binomial, then the 
     specifics of the experiment have no bearing on the numerical 
     results. (In statistical parlance, any methods or procedures 
     that yield raw data are called experiments.) In our TV 
     example, the number of trials (the sample size) is 10, and 
     the probability of success is 0.9. These 2 data are 
     sufficient to calculate the probability distribution for this 
     specific case. Let us consider

[[Page 5384]]

     now an example of PTC in which these specifics are the same 
     as described above. The PTC design prescribes 10 slide test 
     sets (number of trials). A cytologist who performs routine 
     screening and customarily renders accurate diagnoses 9000 
     times among 10,000 screened slides has an approximate true 
     score of 0.9. (In other words, the probability of success is 
     0.9.) When this cytologist attempts to pass this particular 
     PTC, then the probability distribution of the possible 
     correct answers will be identical to the probability 
     distribution observed in the TV example, because the 
     specifics of the TV experiments are the same. If this 
     hypothetical cytologist attempts the test many times, then he 
     or she will read 10 slides correctly in 35% of the tests, 9 
     slides correctly in 39% of the tests, and so on. The 
     numerical values in the 2 experiments are identical.
       We also should note that, if an examinee reads 10 slides or 
     9 slides correctly:which happens in 74% of events under the 
     circumstances described above, then he or she passes the 
     test. However, this individual, who essentially has an 
     adequate true score, will fail a dichotomous PTC 26% of the 
     time because of the low validity and reliability of the test. 
     The phenomenon of failure in this case can be called ``type 1 
     error.'' (The null hypothesis is that ``the cytoscreener is 
     competent.'') A valid and reliable test is expected to pass 
     virtually all cytoscreeners with true scores on the 0.9 
     level; however, any dichotomous test that consists of 10 
     slides or challenges will misclassify approximately 26% of 
     such individuals. It is obvious that this test does not 
     really meet the expectation to determine the competence of an 
     examinee who had a true score of 0.9.
       It needs to be reiterated here that binomial calculations 
     can be performed only for dichotomous tests. The 
     probabilities for some well ordered, nondichotomous tests may 
     be calculated by the use of more complicated multinomial 
     assessments.


             Limitations of the Simple Binomial Error Model

       The binomial error model provides only a rough appraisal of 
     the statistical factors that need to be taken into account in 
     the design of PTC. One of the drawbacks of the model, as 
     mentioned above, is that it is applicable only to dichotomous 
     testing systems. However, the simplicity, transparency, and 
     mathematical calculability of dichotomous setups 
     counterbalance every other consideration. The dichotomous 
     test design makes it possible to assess the impact of test 
     set size on test validity and reliability and to calculate 
     confidence intervals. Thus, the use of a dichotomous test 
     would confer greater predictability and practicability to 
     PTC. The effects on test validity and reliability of a 
     haphazard design, like the CLIA'88-mandated PTC, hardly are 
     calculable by scientific-statistical means. We do not state 
     that dichotomous designs would solve every problem inherent 
     in every type of test, including PTC. However, given that all 
     other conditions of the testing are equal, dichotomous tests 
     have insurmountable advantages over nondichotomous tests.


            Size of Test Sets and Rate of Misclassification

       Figures (not shown) illustrate the probability 
     distributions of correct diagnoses for variable test set 
     sizes and for examinees with different theoretical ``true 
     scores.'' An ideal and flawless PTC would fail all examinees 
     with true scores of 0.85, but no test design can fulfill such 
     requirements. The reliability of the tests improves, however, 
     as the test sets get larger. For examinees with true scores 
     of 0.85 or 0.8, the accuracy of the test increases in 
     parallel with the increasing size of the test sets. (The 
     failure rates become larger for larger test sets.)
       Visualization of the effect of sample size on 
     misclassification also is possible by tabulation. The more 
     slides the test set contains, the lower the misclassification 
     rate. There appear to be anomalies at the set sizes of 9 and 
     19, in which the misclassification rate decreases for 
     examinees with low true scores and increases for the more 
     competent examinees. A test set that consists of 9 or 19 
     slides would be a very impractical choice. If the passing 
     level is set at 90% (eg, 9 correct answers for 10 slides in 
     dichotomous tests), as it is the general practice for PTCs, 
     then 1 error is allowed for a 10-slide set. Under these 
     circumstances, to pass a test based on 9-slide sets with a 
     90% passing grade would be incomparably more difficult than 
     to pass a test based on a 10-slide set, because a single 
     mistake would mean an error >10% and, consequently, a 
     failure. The situation is similar for 19- or 29-slide sets. 
     The greater grade of difficulty with a 9-slide test set is 
     reflected in the smaller passing rates for both competent and 
     less competent examinees. (This circumstance, paradoxically, 
     improves the accuracy of the test for the participants with 
     low true scores.) For these reasons, if the passing level is 
     set at 90%, then only decimal-based test set sizes (10, 20, 
     30, etc. slides or challenges) should be used.
       Another observable phenomenon is the ``law of diminishing 
     returns,'' in which, as the number of slides in the test sets 
     is increases, the misclassification rates decrease. However, 
     the rate of decrease is not level but trails off with 
     increasingly larger set sizes. For instance, 
     misclassification of examinees with a true score of 0.8 is 
     almost halved, from 38% to 20%, when the number of slides in 
     the sets increases from 10 to 20. The next step, from a 20-
     slide set to a 30-slide set, is accompanied by a smaller 
     relative improvement, and so on.
       An important conclusion that can be drawn is that, when the 
     number of slides is increased in the test sets, the decrease 
     in the misclassification rate is more precipitous if the true 
     score is 0.8 or 0.85, ie, on the side of the table for less 
     competent examinees, than if the true score is 0.95. From our 
     viewpoint, this is an advantage. The basic purpose of PTC is 
     not the confirmation of the proficiency of the average 
     cytologist who performs well but the identification of 
     individuals who may have problems with expertise and need 
     remediation. The type 1 error, the failure of competent 
     examinees, is less consequential than the type 2 error, the 
     passing of less competent examinees. The simple binomial 
     model is more suitable to investigate the latter than the 
     former in the set-size ranges that are prevalent in the 
     practice of PTC.


     What Should Be the Minimal Number of Test Slides in Test Sets?

       The question about the minimal number of test slides in 
     test sets could be formulated more accurately as follows: 
     What should be the minimal number of test slides so that we 
     can be 90% confident that the test result is accurate? This 
     type of calculation is relatively simple to perform if the 
     test is dichotomous. In our calculations, we assumed a 
     dichotomous test and 90% as the passing level for the 
     observed score.
       The minimum necessary number of test slides depends to a 
     large extent on the competence of the individual examinee. 
     For a cytologist with very poor skills, a relatively small 
     test set would suffice. However, the discriminatory power of 
     PTC decreases at the point where the skills of the examinee 
     are almost satisfactory but still insufficient. Therefore, 
     for such an individual, the test sets should be much larger 
     if we want 90% confidence. It would be unrealistic to expect 
     any test to differentiate easily between an ``incompetent'' 
     cytologist whose true score is 0.89 and a ``competent'' 
     cytologist with a true score of 0.9.
       Just to illustrate a possible solution, we calculated the 
     minimal size of test sets for examinees who had a true score 
     of 0.8. We wanted to have 90% confidence in the accuracy of 
     the test result. (This means that at least 90% of examinees 
     with a true score of 0.8 will fail the test if the test set 
     contains the calculated number of test slides.) Similar 
     calculations were performed for examinees who had a true 
     score of 0.85.
       For the calculation, we used the algorithm written by the 
     Vassar Education Department, which is in the public domain 
     and may be found on the Internet. According to the results, a 
     40-slide set would provide >90% confidence (exactly, 92.409% 
     confidence) in the accuracy of the results for examinees with 
     a true score of 0.8. A 30-slide set would provide only an 
     87.729% confidence level for these individuals.
       For examinees with a true score of 0.85, much larger test 
     sets would be necessary to provide 90% confidence in the 
     results. A test set consisting of 90 slides would provide 
     88.468% confidence, and only the use of a 100-slide test set 
     would ensure >90% confidence (exactly, 90.055 confidence) in 
     the test results. The extent of the confidence intervals can 
     be easily visualized. Lord et al. presented the 90% 
     confidence intervals for a 30-item dichotomous test on 
     different true score levels.
       The numbers provided above are given only for illustrative 
     purposes. It is obvious that test sets consisting of 100 
     slides, or even 40 slides, could not be used under the 
     generally accepted conditions of PTC. Evidently, only a 
     board-type, full-day, or 2-day-long examination would satisfy 
     the statistical requirements for an accurate and equitable 
     test. Conversely, because such a board-type test would 
     determine the capabilities of the examinees with a high level 
     of accuracy, it would become safe to increase the intertest 
     interval to 8 years or 10 years.
       However, if most aspects of the current federal regulations 
     for PTC remain in force--in other words, if a highly 
     inaccurate and unreliable test also will be used in the 
     future--then it will not be advisable to increase the yearly 
     interval between tests very much. The main reason for this is 
     that short tests are incapable of accurately identifying 
     examinees with low professional skills. Competent examinees 
     who fail the test (type 1 error) pass the test on the second 
     or third attempt with a high probability. Most of these 
     valuable professionals are not harmed much beyond the 
     inconvenience of repeated testing. In contrast, examinees 
     with questionable skills who pass the test (type 2 error) do 
     not have to submit to repeat testing, and they continue to 
     screen patient slides without censure at least until the next 
     test. Of course, it may be argued that, if the test were 
     totally useless, then increasing the interval between test 
     events would not have any effect on public health. However, 
     if the test were totally useless, then the only honest course 
     to follow would be the complete abolishment of PTC. In our 
     opinion, the test in its present form is not totally useless. 
     The

[[Page 5385]]

     current test will force a certain number of cytologists with 
     very poor professional skills (regardless of their low 
     proportion in the entire cytopathology community) to 
     recognize their deficiencies, to participate in 
     remediation(s), and at least to attempt to improve their 
     professional skills. However, as made obvious in the 
     discussion above, the federally mandated PTC in its current 
     form is not able to identify all cytologists with very poor 
     skills. Allowing such individuals, unidentified by the test, 
     to continue screening constitutes a certain danger for the 
     public. If we try to make the current PTC useful at least to 
     some degree, then we should not increase the time interval 
     between tests to 3 or 4 years.


   The High Passing Rate of less Skilled Professionals in Short Tests

       Through the use of the simple binomial model, it also is 
     possible to calculate the number of less than competent 
     individuals who eventually will pass the short tests after 
     repeated attempts. For instance, among 100 examinees who have 
     true scores in the less competent range of 0.85, 54 
     individuals will pass a dichotomous test that consists of 10 
     test slides on the first attempt. The remaining 46 examinees 
     will attempt the test a second time, and 54% of them (ie, 25 
     individuals) will pass on this second try. The remaining 21 
     examinees will attempt the test a third time, and 54% of them 
     (ie, 11 individuals) will pass. In summary, 54 + 25 + 11 = 90 
     of these less-skilled examinees among 100 who were supposed 
     to be identified by the system will avoid serious 
     consequences if a short, 10-slide-based dichotomous test with 
     3 permitted retakes is used.
       A similar calculation illustrates that, among 100 examinees 
     with true scores of 0.8, 76 individuals eventually will pass, 
     if 3 attempts are allowed, in a 10 slide-set, dichotomous PTC 
     system.
       These numbers indicate all too clearly the utter 
     uselessness of short dichotomous PTCs in terms of capability 
     to identify less skilled cytologists. However, we do not go 
     so far as to declare that short PTC systems, dichotomous or 
     nondichotomous, are totally lacking in utility. Even a short 
     test generates interest, creates opportunity for self-
     assessment, and possibly highlights deficiencies in some 
     areas in the professional knowledge of the individual 
     cytologist. This effect should be perceived as beneficial. 
     Our personal experience indicates that very short educational 
     tests, although they may not be suitable in themselves as 
     statistical assessments of professional knowledge of 
     individuals, almost always provide a welcome impetus for 
     continuing education. A short PTC, as an educational 
     experience, may remain a valuable quality-assurance method, 
     although it is limited in scope. In this regard, other 
     valuable educational activities, such as the CAP Pap program, 
     have their full justification. However, we in the 
     cytopathology community should persevere in our attempts to 
     prevent the deleterious situation in which PTC remains an 
     expensive and rather meaningless ritual; a test that, on 
     repeated attempts, can be passed by virtually all competent 
     cytologists, as expected, and also by a very high percentage 
     of those who would be adjudged incompetent if a more reliable 
     testing process were available.


                     Statistics Are Not Everything

        A more intensive integration of statistical principles 
     would be needed to make the current design of PTC more 
     functional. However, we do not believe that, even if 
     statistical principles were applied optimally to PTC, all of 
     the inherent problems of testing could be eliminated. There 
     are many nonstatistical facets of all tests, including PTC. 
     For instance, because, in cytopathology, we are confronted 
     with the morphologic manifestations of extremely complicated 
     biologic systems, total equivalence in the difficulty of test 
     challenges (that is, absolute conformity of corresponding 
     slides in different test sets) cannot be achieved. Perhaps 
     this can be overcome with computerized digital tests to some 
     extent in the future.


Lessons From the Simple Model of Dichotomous PTC That Can Be Applied to 
                    the Dysfunctional Federal Design

       We emphasize once more that the discussions and 
     calculations above are based on the relatively simple model 
     of dichotomous proficiency testing. The current CLIA'88-
     mandated test, with its elaborate scoring system and multiple 
     diagnostic categories, is much more complicated; therefore, 
     our conclusions cannot be transferred to it in any 
     straightforward or easy way. The proportions of expected 
     misclassification rates, the widths of confidence intervals, 
     and other statistical parameters in nondichotomous systems 
     cannot be calculated accurately by using the simple binomial 
     model. In other words, the generalizability (``external 
     validity'') of the foregoing statistical considerations to 
     nondichotomous systems could be questioned. The Galtonian 
     regression toward the mean in the results of the first year 
     of the CLIA'88-mandated test, however, provides indirect 
     evidence that misclassification by the federal test is 
     substantial, and its magnitude is in the range indicated by 
     the simple binomial model. Therefore, it is plausible that 
     the conclusions of the statistical considerations outlined 
     above are applicable to the federally mandated PTC to a large 
     extent.
       We emphasize that the theoretical underpinnings of PTC are 
     much more complex than may be perceived readily. We hope 
     that, if mandatory, nationwide PTC remains in any form, then 
     it is redesigned to be a valid and reliable proficiency 
     testing system or possibly a board-type examination. We 
     believe that accomplishing this would require the engagement 
     of both cytologists and experts who are well versed in the 
     practical and theoretical aspects of modern test theory. This 
     does not mean that more descriptive data from the existing 
     results of the CLIA'88-mandated PTC should be collected. On 
     the contrary, because the design of the CLIA'88-mandated test 
     is flawed, little true insight may be gained by amassing and 
     further studying descriptive data from such a source. Rather, 
     we advocate the careful application of more inferential or 
     theoretical statistics, which would allow a fairer conceptual 
     design of PTC while leaving the final decisions in the hands 
     of expert cytopathologists and cytotechnologists who are 
     familiar the wider aspects of our difficult discipline.

  I also want to thank all of the members of the Women's Caucus. 
Without their wonderful support, I don't know where we would be at this 
point. And I thank, once again, Congressman Deal, the ranking member of 
the subcommittee; Chairman Pallone and Chairman Dingell and Ranking 
Member Barton.
  Madam Speaker, as has been described by my colleagues, in 1998 the 
CLIA, or the Clinical Laboratory Improvement Amendments, went into 
effect. The law was passed. And it took them 4 years for the provision 
to evaluate the performance of laboratories interpreting Pap tests or 
Pap smears to be put into law or to have the rule finalized by Health 
and Human Services. The problem is that program then sat on the shelf 
for 13 years. So in 2005 the rules were then put into effect and 
enforced. And therein lies the program.
  This program currently in place is based upon more than a decade old, 
even 15, 16 years old, 1992, regulatory approach that doesn't reflect 
the modern science and real-world laboratory practice. It does little 
to help patients or physicians charged with caring for them. The 
approach of relying on government-driven individual proficiency testing 
to evaluate the quality of Pap smear interpretations is both outdated 
and not cost effective.
  So the solution is within the bill that we have before us today, H.R. 
1237. There's a companion bill, Madam Speaker, over in the Senate, S. 
2510, and I'm hopeful, as Congressman Deal said, that we will be able 
to get this legislation through both Chambers during this session.
  The Cytology Proficiency Improvement Act modifies CLIA by suspending 
the current regulation that subjects pathologists and others who screen 
for cervical cancer to annual proficiency testing and instead requires 
annual continuing medical education that would provide laboratory 
professionals opportunities to improve their screening and 
interpretation skills in a nonpunitive environment. The bill allows for 
an orderly phase-out of the current program and establishes reasonable 
timelines for the implementation of the new program. The educational 
approach is consistent with that included in the Mammography Quality 
Standards Act, a program that is remarkably effective. So the bill 
would ensure continuing education keeps up with the technology in the 
field and that clinicians are using day after day after day to help 
save lives of Americans all across our Nation. This is a major move in 
the right direction.
  I want to thank once again all of those involved and encourage my 
colleagues to support the bill.
  Mrs. CAPPS. Madam Speaker, I continue to reserve the balance of my 
time.
  Mr. DEAL of Georgia. Madam Speaker, I urge the adoption of the bill.
  Madam Speaker, I yield back the balance of my time.
  Mrs. CAPPS. Madam Speaker, I have no further requests for time and 
again would like to commend my colleagues Representative Gordon and 
Representative Deal and also the Women's Caucus for their much hard 
work and commitment on this important piece of legislation.
  This bill would improve the quality of women's health care, and I 
strongly encourage all of our colleagues to join in support of H.R. 
1237.

[[Page 5386]]


  Mrs. MYRICK. Madam Speaker, I rise today in support of H.R. 1237, the 
Cytology Proficiency Improvement Act. I am pleased to see that the 
House will vote today on revamping a 16-year-old CMS regulation--from 
1992--that calls for a Federal program to test the proficiency of 
individual laboratory professionals who read Pap tests.
  I first became aware of the need to revisit this outdated regulation 
several years ago, in 2005, when CMS first began implementation of the 
program long after it was first put on the books. Congress knows well 
that promulgating regulations and implementation can do more harm than 
good.
  The current oversight model that CMS is using is intended to help 
ensure that Pap tests are being read accurately--to improve public 
health. However, the approach established more than a decade ago, and 
being used today, doesn't necessarily protect women, improve quality or 
further our fight against cervical cancer.
  H.R. 1237 provides an alternative. It redirects the current 
``testing'' scheme to require pathologists and other lab technicians 
who read Pap tests to participate in an annual continuing medical 
education, CME program where their skills would be assessed and where 
the latest advances in Pap test practice could be shared. It would 
complement extensive Pap test quality controls that labs must already 
meet under the Clinical Laboratory Improvement Act. The Mammography 
Quality Standards Act includes a similar CME approach.
  I've talked to pathologists in my district to better understand what 
it would take to add value to their profession, rather than just more 
red tape. Dr. Jared Schwartz was one of those who educated me and lent 
his expertise. He is now serving as president of the College of 
American Pathologists and is a strong advocate for ensuring access to 
Pap tests for all women. The laboratory and medical community support 
this bill, and I'm pleased to support it.
  Mr. BUCHANAN. Madam Speaker, I rise today in support of H.R. 1237, 
the Cytology Proficiency Improvement Act of 2007. I am a cosponsor of 
this important legislation, which enhances women's health by 
establishing a continuing medical education requirement for 
pathologists and laboratory professionals who examine Pap tests to 
screen for cervical cancer.
  I recently toured Sarasota Pathology and heard directly from my 
constituents about the importance of this bill and its potential to 
help save lives.
  This legislation amends the Clinical Laboratory Improvements 
Amendments of 1988, CLIA, which mandated a cytology proficiency test to 
be administered by the Federal Government. However, the program lay 
inactive until 2005, which, because of scientific advancements makes 
the test obsolete and out of date.
  Unlike the current CLIA testing model, H.R. 1237, with its annual 
continuing medical education requirement, will provide the means to 
increase the skills necessary to identify potential cervical cancer, 
and will keep pace with new science.
  H.R. 1237 is modeled after the Mammography Quality Standards Act, 
MQSA, which was passed in 1992. That bill ensured women would have 
access to quality mammography procedures. This bill requires similar 
educational testing for pathologists.
  The American Medical Association, the College of OBGYNs, the College 
of American Pathologists, the American Society for Clinical Pathology, 
the College of Nurse Midwifes, and the Cancer Research and Prevention 
Foundation endorse the bill.
  Finally, I want to mention that the Congressional Budget Office has 
determined that it will not cost the Federal Government any additional 
expenditure.
  Madam Speaker, I urge my colleagues to join with me in support of a 
bill that will greatly improve the quality of women's health care in 
America.
  Mr. CASTLE. Madam Speaker, I rise today in support of The Cytology 
Proficiency Improvement Act, H.R. 1237, which would modernize and 
improve a Federal program aimed at promoting quality cervical cancer 
screening. Pathologists are already required by Federal law under the 
Clinical Laboratory Improvement Amendments of 1988, CLIA, to comply 
with extensive quality assurance standards for Pap tests. The bill 
would complement CLIA by establishing a Federal continuing medical 
education, CME, requirement for pathologists and laboratory 
professionals who examine Pap tests to screen for cervical cancer.
  I have been a long-time advocate of medical technology and education 
advancements. Earlier this year, I had the opportunity to tour the 
Pathology Lab at St. Francis Hospital in Wilmington, DE to get a first 
hand look at the practice and techniques used in Delaware. During the 
tour, the doctors and medical staff highlighted the need for H.R. 1237.
  Regular screening can make all the difference in addressing cervical 
cancer and early detection can save lives. Women need access to the 
latest in Pap test science, principles of patient safety and 
technological advances such as computer-assisted screening, digital 
imaging, and HPV typing. Over the years, this educational requirement 
will also accommodate advances in science and technology without going 
through the long process of making changes in regulation.
  I urge my colleagues on both sides of the aisle to support passage of 
The Cytology Proficiency Improvement Act, H.R. 1237.
  Mrs. CAPPS. Madam Speaker, I yield back the balance of my time.
  The SPEAKER pro tempore. The question is on the motion offered by the 
gentlewoman from California (Mrs. Capps) that the House suspend the 
rules and pass the bill, H.R. 1237, as amended.
  The question was taken; and (two-thirds being in the affirmative) the 
rules were suspended and the bill, as amended, was passed.
  A motion to reconsider was laid on the table.

                          ____________________